iSBEM: An Open-Source Workflow for Automated ROI Targeting in Volume Electron Microscopy

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Authors: Paolo Ronchi, Graham Ross, Alana Burrell, Joost de Folter, Yanneck Klenz, Nedal Darif, Fiona Young, Matthew Lawson, Jonas Albers, Tobias Pietz, Friedrich Frischknecht, Elizabeth Duke
+4 more Candice Roufosse, Lucy Collinson, Amy Strange, Yannick Schwab
Cited by: 1
References: 34

Abstract

Abstract Serial Block Face – Scanning Electron Microscopy (SBF-SEM) is a volume EM method suited to investigate the 3D architecture of tissues and even entire organisms at high resolution. However, imaging large volumes in their entirety is time-consuming and not always necessary. Many research projects have a focused interest in well-defined sub-regions of the samples. The targeting and acquisition of such regions of interest (ROIs) are however currently conducted in a manual way and require heavy involvement of experienced operators. We present a workflow and an original open-source software tool (iSBEM), which allow automated targeting of ROIs in a large tissue sample, based on X-ray microscopy (XRM) maps. After an initial ROI identification and registration of the XRM map with the sample mounted on the SBF-SEM stage, iSBEM takes over the control of the microscope, triggering high resolution acquisitions at defined ROI positions, with minimal user intervention. We demonstrate the approach on two biologically distinct specimens — malarial oocysts in infected mosquito midgut tissue, and immune cells in human kidney biopsies — achieving significant improvement in acquisition throughput relative to manual operations, without compromising targeting precision. We also showcase the workflow in a correlative light-Xray-electron microscopy setup, which allowed us to further improve the correct target definition.

Fields of Study & Subjects

Advanced Electron Microscopy Techniques and Applications Electron and X-Ray Spectroscopy Techniques Advanced X-ray Imaging Techniques

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Publication date
6 June 2026
Document type
Preprint